An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology

Detalhes bibliográficos
Autor(a) principal: De Oliveira, J. P. [UNESP]
Data de Publicação: 2001
Outros Autores: Oki, N. [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/MWSCAS.2001.986285
http://hdl.handle.net/11449/66666
Resumo: This paper describes a analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a gaussian function obtained through the characteristic of the bipolar differential pair. The gaussian parameters (gain, center and width) is changed with programmable current source. Results obtained with PSPICE software is showed.
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spelling An analog implementation of radial basis neural networks (RBNN) using BiCMOS technologyCMOS integrated circuitsComputer softwareElectric currentsGain measurementNeural networksNumerical methodsVLSI circuitsBiCMOS technologyGaussian functionProgrammable current sourceRadial basis neural networksIntegrated circuit manufactureThis paper describes a analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a gaussian function obtained through the characteristic of the bipolar differential pair. The gaussian parameters (gain, center and width) is changed with programmable current source. Results obtained with PSPICE software is showed.Univ. Estadual Paulista - UNESP Departamento de Engenharia Electrica, 15385-000 Ilha Solteira - SPUniv. Estadual Paulista - UNESP Departamento de Engenharia Electrica, 15385-000 Ilha Solteira - SPUniversidade Estadual Paulista (Unesp)De Oliveira, J. P. [UNESP]Oki, N. [UNESP]2014-05-27T11:20:20Z2014-05-27T11:20:20Z2001-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject705-708http://dx.doi.org/10.1109/MWSCAS.2001.986285Midwest Symposium on Circuits and Systems, v. 2, p. 705-708.http://hdl.handle.net/11449/6666610.1109/MWSCAS.2001.986285WOS:0001759717001582-s2.0-00355752921525717947689076Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengMidwest Symposium on Circuits and Systemsinfo:eu-repo/semantics/openAccess2021-10-23T21:41:31Zoai:repositorio.unesp.br:11449/66666Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T21:41:31Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
title An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
spellingShingle An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
De Oliveira, J. P. [UNESP]
CMOS integrated circuits
Computer software
Electric currents
Gain measurement
Neural networks
Numerical methods
VLSI circuits
BiCMOS technology
Gaussian function
Programmable current source
Radial basis neural networks
Integrated circuit manufacture
title_short An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
title_full An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
title_fullStr An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
title_full_unstemmed An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
title_sort An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
author De Oliveira, J. P. [UNESP]
author_facet De Oliveira, J. P. [UNESP]
Oki, N. [UNESP]
author_role author
author2 Oki, N. [UNESP]
author2_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv De Oliveira, J. P. [UNESP]
Oki, N. [UNESP]
dc.subject.por.fl_str_mv CMOS integrated circuits
Computer software
Electric currents
Gain measurement
Neural networks
Numerical methods
VLSI circuits
BiCMOS technology
Gaussian function
Programmable current source
Radial basis neural networks
Integrated circuit manufacture
topic CMOS integrated circuits
Computer software
Electric currents
Gain measurement
Neural networks
Numerical methods
VLSI circuits
BiCMOS technology
Gaussian function
Programmable current source
Radial basis neural networks
Integrated circuit manufacture
description This paper describes a analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a gaussian function obtained through the characteristic of the bipolar differential pair. The gaussian parameters (gain, center and width) is changed with programmable current source. Results obtained with PSPICE software is showed.
publishDate 2001
dc.date.none.fl_str_mv 2001-12-01
2014-05-27T11:20:20Z
2014-05-27T11:20:20Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/MWSCAS.2001.986285
Midwest Symposium on Circuits and Systems, v. 2, p. 705-708.
http://hdl.handle.net/11449/66666
10.1109/MWSCAS.2001.986285
WOS:000175971700158
2-s2.0-0035575292
1525717947689076
url http://dx.doi.org/10.1109/MWSCAS.2001.986285
http://hdl.handle.net/11449/66666
identifier_str_mv Midwest Symposium on Circuits and Systems, v. 2, p. 705-708.
10.1109/MWSCAS.2001.986285
WOS:000175971700158
2-s2.0-0035575292
1525717947689076
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Midwest Symposium on Circuits and Systems
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 705-708
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1799965504507478016

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